JabRef
v6
v6
  • JabRef Bibliography Management
  • Installation
  • Getting started
  • Collect
    • Add entry manually
    • Add entry using an ID
    • Add entry using reference text
    • Searching externally using Online Services
    • Add entry using PDFs
    • Add PDFs to an entry
    • Browser Extension
    • Import
      • Custom import filters
      • Import inspection window
  • Organize
    • Edit an entry
    • Groups
    • Keywords
    • Mark and grade
    • Comment on an entry
    • Searching within the library
    • Complete information using online databases
    • Manage associated files
    • Manage field names and their content
    • Best practices
    • Check consistency
    • Cleanup entries
    • Check integrity
    • Find duplicates
    • Merge entries
    • Save actions
  • Cite
    • BibTeX and biblatex
    • Pushing to external editor application
    • Export to Microsoft Word
    • OpenOffice/LibreOffice integration
  • Share
    • Sharing a Bib(la)TeX Library
    • Shared SQL Database
      • Migration of pre-3.6 SQL databases into a shared SQL database
    • Export
      • Custom export filters
    • Send as email
  • AI functionality
    • AI providers and API keys
    • AI preferences
    • AI troubleshooting
    • Running a local LLM model
  • Configuration
    • Customize the citation key generator
    • Customize entry types
    • Customize general fields
    • Customize key bindings
    • Library properties
    • Entry preview setup
    • Manage external file types
    • Manage protected terms
    • The string editor
  • Advanced information
    • Main Window
    • Entry Editor
      • Links to other entries
      • The Bibtex / Biblatex source tab
      • The 'owner' field
      • Time stamp field
      • LaTeX Citations Tab
    • About BibTeX and its fields
    • Strings
    • Field content selector
    • URL and DOI links in JabRef
    • Command line use and options
    • Automatic Backup (.sav and .bak) and Autosave
    • XMP metadata support in JabRef
    • Remote operation
    • Custom themes
    • Journal abbreviations
    • New subdatabase based on AUX file
    • How to expand first names of an entry
    • Debugging your library file
    • Resources
    • License
    • Knowledge
      • MS Office Bibliography XML format
      • Comparison of the Medline (txt), Medline (xml), and RIS format
      • EndNote Export Filter
  • Frequently Asked Questions
    • Linux
    • Mac OS X
    • Windows
  • JabKit
  • Discussion Forum
  • Contribute to JabRef
    • How to Improve the Help Page
    • How to translate the JabRef User Interface
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On this page
  • Parser Explanation
  • Rule-based
  • Grobid
  • LLM

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  1. Collect

Add entry using reference text

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Last updated 5 days ago

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Entries can be created from a reference text.

In case you have a reference string, JabRef offers the functionality to convert the text to BibTeX (or biblatex).

Different parsers will lead to different results. It is strongly recommended to fact-check all conversions, regardless of parser choice. All of them can confabulate. For comparison, is much more reliable and accurate.

Example:

O. Kopp, A. Armbruster, und O. Zimmermann, "Markdown Architectural Decision Records: Format and Tool Support", in 10th ZEUS Workshop, 2018.
  1. Click Library and select "New entry from plain text..." Alternatively, you can press Ctrl+Shift+N.

  2. The "Plain Reference Parser" window opens

  3. Paste the reference text:

  4. Choose a parser from the drop-down menu.

  5. Click "Add to current library"

  6. The result is selected in the entry table:

Parser Explanation

Rule-based

This is the default parser. It does not require any extensive setups, nor does it send data to remote services. Any conversions are executed locally on your device. The rule-based parser also is deterministic, as the rules are hard-coded. Unfortunately, at time of writing, the rule-based parser is far from perfect. As one can see in the example above, the number "10" was wrongly interpreted as a page number, which is clearly not the intended result. The underlying rules are insufficient to account for all possibilities that bibliographic metadata may contain and ideally would require a way more fine-grained, but an ever more complex rule-set. It is recommended to use the rule-based parser as a last-resort, when the Grobid or LLM based parsers are not available or not desireable.

Grobid

LLM

JabRef uses the technology offered by , a machine learning software project with decades of experience and development dedicated to bibliographic metadata extraction. The Grobid parser usually tends to achieve better results than the rule-based parser. Since JabRef runs Grobid on a remote instance, users will have to confirm sending data to JabRef's online service in the preferences (File > Preferences > Web search > Remote Services). Sending data is disabled by default. It cannot be guaranteed that JabRef's Grobid instance will always be up and running, but it is possible for you to set up your .

Large Language Models too can be used to convert the reference text. The quality of the results is surprisingly good, tends to be better than the rule-based parser and competes with Grobid. Nevertheless, it depends on the model or service that is used and if they are trained/designed for this use-case. Extensive documentation about how to set up a local LLM or connect to a remote AI service can be found in the section. Data privacy depends on the external application that you are using to run the local model and/or on the remote AI provider, if you are connecting to one of those.

Grobid
own Grobid Instance
AI functionality
adding entries using an ID
Grobid related preference section in JabRef